Recently, an effort for a smart community is intensified. In a smart community, various urban infrastructures, such as electricity and traffic, are integrated and managed using an IT technology, and an urban development to optimize energy usage as a whole city or local area is set as a goal. An example application of the smart community is a demand-response (hereinafter, referred to as DR).
The DR is a mechanism which induces or promotes a reduction of the quantity of power usage at the power consumer's end, such as a house or a building, mainly when the need for reduction of power consumption becomes apparent like when a power demand/supply balance becomes tight, thereby realizing an optimized energy usage as a whole city or local area. The way of realizing such a mechanism is to increase a purchased power unit price, or to give an incentive in accordance with the reduced quantity of the power usage.
In the case of, in particular, a large-scale building, even if a part of the quantity of power usage is reduced by the DR, an impact applied to the local energy demand/supply is remarkable. In addition, according to the DR, when electricity/heat storage facilities that can store electric energy or thermal energy are utilized, a time at which the energy demand/supply should be balanced can be shifted.
“Electricity/heat storage” in electricity/heat storage facilities is to utilize the energy storage capacity of batteries and heat storage tanks, and to utilize electricity storage or heat storage, or, both of them. That is, the electricity/heat storage facilities are energy storage devices which have an important role as power adjusting power in order to optimize the energy usage as a whole local area.
To control various devices installed in a large-scale building, there is an operation schedule optimizing device that optimizes the operation schedules of the control-target apparatuses in accordance with a predetermined evaluation barometer. In this case, various devices to be controlled by the operation schedule optimizing device include, in addition to energy storage devices like the aforementioned electricity/heat storage facilities, energy supply devices and energy consuming devices. Patent Document 1 discloses a technology of optimizing the operation schedule of a device while reducing the energy consumption, reducing the power consumption, reducing the energy costs, and minimizing the quantity of CO2 emission.
Meanwhile, according to the DR, an incentive that is a cost-benefit performance is important, and it is necessary to clarify the quantity of power usage reduced by a consumer in order to fairly determine such an incentive. Hence, a reference value to the quantity of power usage by a consumer is defined in many cases. The reference value to the quantity of power usage will be referred to as a base line.
The base line is an expected value of the quantity of power usage by a consumer when the quantity of power usage is not reduced by the DR, and is calculated based on the actual values of the quantities of power usage by a consumer within a past certain time period mainly when no DR was applied. That is, according to DR, a reduced quantity of power is obtained in accordance with a difference between the base line and the actual value of the quantity of power usage when the DR was applied, and thus an incentive is set. Hence, according to the DR, it is necessary to precisely and quantitatively predict the quantity of power usage in order to optimize the operation schedule of a device.
In practice, however, various unexpected events occur, and it is difficult to precisely predict the quantity of power usage. Example unexpected events are a breakdown of a co-generation or power generation facilities including a PV, an output fluctuation, and a change in the demand quantity of power and heat. When those events occur, a dissociation different from the prediction presumed in advance inevitably occurs, and thus the quantity of power usage becomes out of the predicted range.
Hence, it is necessary to review the operation schedule of a device appropriately in accordance with a situation time by time, and to adjust the predicted value of the quantity of power usage. Therefore, a technology of comparing an actual value of a given item at a predetermined operation timing with the predicted value in advance of that item, and of reviewing the operation schedule of a control-target apparatus based on the comparison result is expected. According to such an operation schedule optimizing technology, when a deviation between the actual value and the predicted value becomes larger than a preset threshold, it is determined that a dissociation different from the prediction presumed in advance occurs, the operation schedule of the control-target apparatus is reviewed, and the operation schedule is optimized again.
According to the above-explained technology, however, the setting of the threshold is difficult. For example, it is presumed that the heat storage remaining level of a heat storage tank is reduced beyond the predicted scheduled value, and the heat storage remaining level becomes zero within a time period corresponding to a DR target time. When such a situation is predicted, the operation schedule of the device must be reviewed so as to compensate the shortage of the heat supply quantity while maintaining a desired power reduction quantity expected in the presumed schedule. Note that a DR target time is a time subjected to a reduction of the quantity of power usage by the DR.
However, how the actual power reduction quantity changes when the remaining heat storage quantity becomes zero varies depending on the following factors. A change in the power reduction quantity is determined based on various factors, such as the shortage quantity of heat, the kind of a heat-source device in operation, and that of a heat-source device additionally actuated, and characteristics thereof. When, for example, a heat-source device in operation is a gas heat source, and is partially loaded and operated. In this case, if the shortage quantity of heat is smaller than the available capacity thereof, it is sufficient if only the output by the gas heat source is increased, and the operation can be maintained without increasing the quantity of power usage.
Conversely, when the gas heat source is operated with a rated load, it is necessary to additionally actuate other heat-source devices. At this time, if the additionally actuated heat source device is an electric heat source, the quantity of power usage in the whole building rightfully increases in accordance with the characteristic of such a heat source and the heat supply quantity thereof. Hence, when a situation different from the prediction presumed in advance occurs, how the quantity of power usage in the whole building changes in future varies depending on a situation time by time. Accordingly, in order to optimize the operation schedule, when the threshold is uniquely set, it is difficult to flexibly cope with a situation changing time by time.
Therefore, there is proposed a technology of, not setting the threshold, but of setting an updating timing of the operation schedule, and reviewing the operation schedule at the set timing using the latest actual value. According to this technology, the setting of the threshold becomes unnecessary, and thus it is the simplest method as the operation schedule optimizing technology that can cope with an occurrence of an event different from the prediction presumed in advance if there is no constraint of a calculator, etc., that repeatedly calculates the operation schedule.